Análisis espacio-temporal de las condiciones climáticas en la zona central del Litoral ecuatoriano y su relación con el rendimiento de melina (Gmelina arborea Roxb.). - Zambrano Palma, Helen Tatiana (2020)
The present research was intended to make a spatial-temporal analysis of the climatic conditions and their relationship with volume yields of Gmelina arborea Roxb plantations. The general objective was to analyze the relationship between temperature and precipitation with the dasometric variables in the melina plantations in the central zone of the Ecuadorian coast. The study was carried out in six farms belonging to the ENDESA-BOTROSA business group. Diameter records of melina plantations, geographical coordinates, temperature and precipitation data were used, obtained a part of the meteorological stations located in the study areas and another part of the NASA geoportals from the Geovanni, CHRS and Wordlclim server. The climatic variability of part of the Ecuadorian coast was determined. Also the regression of correlated components was made to determine more important predictive variables, used later in the model of linear regression made in the statistical program SPSS. The study site, hacienda Toachi, had the highest precipitation and lowest temperature, while hacienda San Carlos had the lowest precipitation and highest temperature in contrast to the other haciendas studied. It was determined that the variables temperature in July and precipitation in November are the most important predictors. With the analysis of the ANOVA of the linear regression model, it was demonstrated the significance among predictive variables and with it it was determined the values to use in the formula to calculate the Annual Average Increase projected for the period 2041-2060, based on scenarios obtained from CHELSA geoportal, it was given as a result that the highest projected IMA will have the San Carlos hacienda with 8.06 cm and Lulo and La Minga with 7.87 cm. This means that the optimal sites for planting melina will be in the cantons of Quevedo and Valencia in the Province of Los Rios. Key words: variability, correlated, dasometric, predictive